Product/Project Manager - Gen Ai

Tech Mahindra; Bengaluru; Hybrid; INR 3,800,000 - 6,000,000; Full time

Job summary

Tech Mahindra in Bengaluru seeks an experienced Product/Project Manager to translate inputs into AI product requirements, build roadmaps, and own lifecycle decisions. The role is hybrid with four days in office, focused on AI use cases, value delivery, and customer outcomes.

The candidate will plan and execute programs, partner with Data Science, ML Engineering, and Software teams, define evaluation criteria, manage risks, and mentor teams to scale AI capabilities from pilot to production.

Qualifications

• Bachelor’s degree in Engineering, Computer Science, Data Science, or a related technical discipline.
• 8+ years of combined product management, program/project management, or technical delivery experience, including 2+ years on AI, ML, data, or analytics initiatives.
• Demonstrated record of delivering at least one AI/ML or data-driven capability into production use with measurable business outcomes.
• Technical fluency in the AI stack, including data pipelines, model training and evaluation, LLM/generative AI patterns, and deployment/MLOps concepts.

Responsibilities

• Translate inputs into AI product requirements, use cases, value propositions, and roadmap recommendations.
• Build fact-based business cases connecting AI capability to customer outcomes, revenue opportunity, cost and margin impact, and strategic fit.
• Prioritize a portfolio of AI use cases on value, feasibility, data readiness, and time-to-impact; make and defend explicit trade-off decisions.
• Own AI product lifecycle decisions, feature prioritization, model and release readiness, adoption barriers, deprecation, and retirement.
• Prepare project plans and drive initiatives from conception to implementation, deployment, and adoption.
• Ensure effective execution to scope, timeline, and budget; track metrics and provide status to stakeholders.
• Manage schedule and task detail using project management tools and dashboards.
• Identify, evaluate, and address program risks; surface complications before commitments.
• Conduct reviews to ensure documentation, models, and solutions are of acceptable quality.
• Partner with Business, Data Science, ML Engineering, Data Platform, and Software teams to ensure requirements are understood and traceable.
• Drive definition of evaluation criteria and acceptance thresholds for AI systems.
• Own the path from pilot to production: MLOps readiness, monitoring, model drift management, and total cost of ownership.
• Engage customer-facing stakeholders to understand high-value problems and capture VOC, escalation learnings, and competitive intelligence.
• Support customer and executive technical reviews with product positioning and evidence-based messaging.
• Identify gaps between current AI capability and customer needs, and propose corrective actions.
• Drive alignment across Business Units, Engineering, IT, Services, and Operations.
• Coordinate launch planning, enablement, change management, adoption tracking, and issue resolution for AI capabilities.
• Maintain documentation of product decisions, assumptions, dependencies, risks, and metrics.
• Use dashboards and reviews to communicate progress and upscale appropriately.
• Mentor and train team members in AI product and program management.

Skills

AI product management

Program management

Technical delivery

Cross-functional leadership

ML/AI

stakeholder comm

Education

Bachelor’s degree in Engineering, CS, DS, or related

Tools

MLOps

Job description

Role - Product Manager/Project Manager/Technical Project Manager

Mode - Hybrid (4 Days working from office)

JD:

KEY RESPONSIBILITIES

• Translate inputs into AI product requirements, use cases, value propositions, and roadmap recommendations.
• Build fact-based business cases connecting AI capability to customer outcomes, revenue opportunity, cost and margin impact, and strategic fit.
• Prioritize a portfolio of AI use cases on value, feasibility, data readiness, and time-to-impact; make and defend explicit trade-off and de-scoping decisions.
• Own AI product lifecycle decisions, feature prioritization, model and release readiness, adoption barriers, deprecation, and retirement.

Program Planning & Execution

• Prepare project plans and drive initiatives from conception and planning through implementation, deployment, and adoption.
• Ensure effective and efficient execution to established guardrails of scope, timeline, and budget; track execution and compliance metrics and provide regular status and feedback to stakeholders.
• Manage schedule and task detail using project management tools, reports, tracking charts, checklists, and scheduling software.
• Identify, evaluate, and address program risks per established guidelines; surface and resolve complications before they impact commitments.
• Conduct appropriate reviews to ensure documentation, models, and solutions are of acceptable quality prior to release.

Technical Partnership & Delivery Quality

• Partner with Business, Data Science, ML Engineering, Data Platform, and Software teams to ensure requirements are understood, feasible, prioritized, and traceable through execution.
• Drive definition of evaluation criteria and acceptance thresholds for AI systems.
• Own the path from pilot to production: MLOps readiness, monitoring, model drift management, support model, and total cost of ownership.

Customer, Field & Competitive Insight

• Engage customer-facing stakeholders and technical experts to understand customer high-value problems and operational pain points.
• Capture and synthesize Voice of Customer, escalation learnings, and competitive intelligence into actionable AI product recommendations.
• Support customer and executive technical reviews with product positioning, technical rationale, and evidence-based messaging.
• Identify gaps between current AI capability and customer needs, and recommend corrective actions or roadmap adjustments.

Cross-Functional Leadership

• Drive alignment of system-level requirements across Business Units, Engineering, IT, Services, and Operations.
• Coordinate launch planning, enablement, change management, adoption tracking, and issue resolution for AI capabilities.
• Maintain clear documentation of product decisions, assumptions, dependencies, risks, and success metrics.
• Use structured operating rhythms, dashboards, and reviews to communicate progress and upscale appropriately.
• Mentor and train team members in AI product and program management practice.

COMPETENCIES

• Functional Knowledge: Demonstrates depth and/or breadth of expertise in own specialized discipline or field.
• Business Expertise: Interprets internal and external business challenges and recommends best practices to improve products, processes, or services.
• Leadership: May lead functional teams or programs with moderate resource requirements, risk, and/or complexity.
• Problem Solving: Leads others to solve complex problems; uses sophisticated analytical thought to exercise judgment and identify innovative solutions.
• Impact: Impacts the achievement of customer, operational, project, or service objectives; work is guided by functional policies.
• Interpersonal Skills: Communicates difficult concepts and negotiates with others to adopt a different point of view.

QUALIFICATIONS

Required

• Bachelor’s degree in Engineering, Computer Science, Data Science, or a related technical discipline; advanced degree preferred.
• 8+ years of combined product management, program/project management, or technical delivery experience, including 2+ years on AI, machine learning, data, or analytics initiatives.
• Demonstrated record of delivering at least one AI/ML or data-driven capability into production use with measurable business outcomes.
• Technical fluency in the AI stack, including data pipelines, model training and evaluation, LLM/generative AI patterns (RAG, agents), and deployment/MLOps concepts, sufficient to lead credible technical trade-off discussions.
• Proven ability to run structured program management: planning, scheduling, financial tracking, risk management, dependency management, and status reporting.
• Ability to translate technical concepts into customer value, product requirements, and cross-functional execution plans.
• Strong written and verbal communication, including concise executive storytelling and trade-off framing.
• Demonstrated ability to drive alignment across diverse organizations without direct authority.

Preferred

• Experience in semiconductor equipment, process technology, services, diagnostics, data platforms, automation, reliability, or advanced manufacturing environments.
• Familiarity with industrial and manufacturing AI applications.
• Hands-on experience using agentic AI tooling to develop concepts, UI prototypes, and dynamic product requirements documents.
• Experience with market requirements specifications, product lifecycle management, launch readiness, pricing inputs, or service product strategy.
• Working knowledge of AI governance, model risk management, data privacy, and export-control considerations in a global enterprise.